Efficient last-mile delivery remains a critical challenge for rural agricultural logistics, globally, particularly in cold-climate regions with dispersed agricultural operations. Truck–drone hybrids can reduce delivery times but face payload limits, cold-weather battery loss, and beyond-visual-line-of-sight regulations. This review evaluates the potential of GIS-enabled truck–drone hybrid systems to overcome infrastructural, environmental, and operational barriers in such settings. This study uses the state of North Dakota (USA) as a representative case because of its cold climate, low density, and weak connectivity. These conditions require different routing and system assumptions than typical regions. The study conducts a systematic review of 81 high-quality publications. It identifies seven interconnected research domains: GIS analytics, truck–drone coordination, smart agriculture integration, rural implementation, sustainability assessment, strategic design, and data security. The findings stipulate that GIS enhances hybrid logistics through route optimization, launch site planning, and real-time monitoring. Additionally, this study emphasizes the rural, low-density context and identifies specific gaps related to cold-weather performance, restrictions to line-of-sight operations, and economic feasibility in ultra-low-density delivery networks. The study concludes with a roadmap for research and policy development to enable practical deployment in cold-climate agricultural regions.

The port being an economical leg of countries development and thereby affected by climate change creates a substantial cost to the various stakeholders since is described as a “business” hub. It is, therefore, essential that ports across the globe attribute much importance to climate adaptation and its relation to port efficiency, especially for the coming years. The need to establish the effect these variables have on each other has become paramount. For this study, an empirical analysis of Ghanaian ports is being reviewed for the past and future annual efficiencies and adaptation scores. The annual efficiencies of both ports are calculated using various variables as inputs and outputs with the DEA Frontier software to calculate the DEA-CCR of the study ports. To assess the adaptation scores of each port, questionnaires and interviews were conducted based on four (4) major factors that affect port adaptation. This research also employs the linear mixed model and one-way ANOVA to assess the means of the data groups obtained for 2009-2020 & 2021-2040 respectively. This research aimed to analyse the significant relationship between port adaptation and efficiency for past and future years while highlighting the adaptative strategies of Ghanaian ports. The concluding chapters of this research represent the data analysis, policy recommendation for the stakeholders of Ghanaian ports, and also recommendations that are deemed useful for further research.